Usually, a sequence of independent and equally distributed random variables is the statistical model adopted to study the design extremes of geophysical loads. However, the autocorrelation function of most loads has significant nonzero values and then a stochastic model should be used. Unfortunately, major conclusions of the stochastic theory of extremes are obtained assuming the studied process is gaussian and several geophysical loads are nongaussian process. Furthermore, most of these results are only acceptable under asymptotic conditions and their validity limits are not well known. In this paper, a nongaussian stationary stochastic process is developed to model geophysical loads in order to obtain the exact distribution of their extremes. A seensitivity analysis of the expected return periods and of their variances with the coefficients of the loads autocorrelation is also presented. As an example, this model is successfully applied to deseasonalized hourly mean wind velocities recorded in Lisbon.